Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
The VP, AI & Digital Workplace leads the enterprise strategy, governance, and operational execution of AI enablement and digital transformation across the organization. This executive is responsible for establishing secure, scalable, and value-driven AI platforms and automation capabilities that accelerate productivity, optimize operations, and deliver measurable efficiency gains across all business units.
This role serves as the enterprise owner of AI platform architecture, tooling, policy, governance, data classification, and responsible AI standards. The VP partners closely with Security, Legal, Data, IT, Engineering, and Business leaders to ensure AI adoption is secure, compliant, and aligned to enterprise risk posture and regulatory requirements.
Success in this role equates to widespread AI adoption, measurable efficiency improvements, strong governance and compliance, and a modern digital workplace that leverages automation and AI-driven insights to reduce friction and unlock enterprise value.
As a senior executive leader, the VP establishes enterprise-wide standards, operating models, and value realization frameworks for AI and automation initiatives. The ideal candidate brings deep expertise in AI platforms, enterprise governance, process optimization, and large-scale transformation, along with a proven ability to drive cultural change and business impact through technology innovation.
What you'll do:
- Enterprise AI Strategy & Platform Enablement
- Develop and execute the enterprise AI strategy and multi-year roadmap aligned to corporate objectives.
- Establish and oversee AI platform architecture, tooling standards, and integration frameworks across the organization.
- Define AI governance models including policy, responsible AI standards, risk frameworks, and regulatory alignment.
- Partner with Security and Legal to implement controls for data classification, data privacy, intellectual property protection, and AI model risk management.
- Evaluate and manage AI vendor ecosystem, including foundation models, copilots, automation platforms, and emerging technologies.
- Governance, Security & Responsible AI
- Establish enterprise AI policy frameworks covering acceptable use, data handling, model lifecycle management, and auditability.
- Implement guardrails for secure AI usage, including access controls, data loss prevention (DLP), logging, monitoring, and compliance enforcement.
- Lead AI risk assessments, bias mitigation strategies, and governance review boards.
- Ensure alignment with cybersecurity, privacy, and regulatory requirements across jurisdictions.
- AI Automation & Process Optimization
- Lead enterprise-wide automation strategy, incorporating AI, RPA, workflow orchestration, and process mining.
- Identify high-value automation opportunities across Finance, HR, Sales, Engineering, Operations, and Corporate functions.
- Oversee deployment frameworks for AI solutions, including pilot validation, scaled rollout, change management, and performance tracking.
- Establish reusable automation patterns and best practices to accelerate adoption and reduce duplication.
- Build AI-enabled service optimization within IT and enterprise support functions.
- Value Realization & Business Impact
- Define and track KPIs tied to AI-driven productivity gains, cost reduction, cycle time improvement, and revenue enablement.
- Establish value realization models that quantify ROI across AI and automation initiatives.
- Partner with business unit leaders to embed AI capabilities into workflows and operating models.
- Develop executive-level dashboards and reporting frameworks to demonstrate measurable impact.
- Drive adoption strategies including enablement programs, training, and AI literacy initiatives
- Organizational Leadership
- Build and scale high-performing teams across AI engineering, automation, governance, and digital workplace transformation.
- Establish performance metrics, operational standards, and maturity models for enterprise AI capabilities.
- Manage departmental budget, investment prioritization, and vendor cost optimization strategies.
- Serve as executive sponsor for digital workplace innovation and AI-driven cultural transformation.
Required qualifications:
- Progressive experience in enterprise technology, digital transformation, or AI-driven innovation.
- Senior leadership or executive roles with enterprise-wide accountability.
- Demonstrated experience leading enterprise AI platform strategy, governance, and secure deployment.
- Deep understanding of AI/ML ecosystems, generative AI technologies, automation platforms, and enterprise architecture integration.
- Experience implementing governance frameworks including policy development, risk management, compliance, and data protection standards.
- Proven track record of delivering measurable efficiency gains and business value through automation and AI adoption.
- Strong financial acumen with experience managing large budgets and ROI-based investment strategies.
- Exceptional executive communication skills with demonstrated ability to influence C-level and board-level stakeholders.
- Experience leading enterprise change management and large-scale adoption programs.
- Owns executive stakeholder relationships, anticipating needs, shaping priorities, and ensuring services deliver measurable value aligned to enterprise goals
Preferred qualifications:
- Experience in regulated or security-sensitive environments requiring strict data governance and compliance controls.
- Experience implementing process mining and enterprise workflow automation platforms.
- Strong background in data classification frameworks and enterprise information security architecture.
- Familiarity with MLOps, model lifecycle management, and AI observability frameworks.
- Experience scaling AI platforms in high-growth or transformation-focused enterprises.
- Advanced degree in Computer Science, Engineering, Data Science, Business, or related field.
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.
